TTD : remove first unrelevant points

climateqa/engine/talk_to_data/plot.py

@@ -81,15 +81,29 @@ def plot_indicator_evolution_at_location(params: dict) -> Callable[..., Figure]:
             years = df_avg["year"].astype(int).tolist()
 
             # Compute the 10-year rolling average
+            rolling_window = 10
             sliding_averages = (
                 df_avg[indicator]
-                .rolling(window=10, min_periods=1)
+                .rolling(window=rolling_window, min_periods=rolling_window)
                 .mean()
                 .astype(float)
                 .tolist()
             )
             model_label = "Model Average"
 
+            # Only add rolling average if we have enough data points
+            if len([x for x in sliding_averages if pd.notna(x)]) > 0:
+                # Sliding average dashed line
+                fig.add_scatter(
+                    x=years,
+                    y=sliding_averages,
+                    mode="lines",
+                    name="10 years rolling average",
+                    line=dict(dash="dash"),
+                    marker=dict(color="#d62728"),
+                    hovertemplate=f"10-year average: %{{y:.2f}} {unit}<br>Year: %{{x}}<extra></extra>"
+                )
+
         else:
             df_model = df
 
@@ -98,15 +112,28 @@ def plot_indicator_evolution_at_location(params: dict) -> Callable[..., Figure]:
             years = df_model["year"].astype(int).tolist()
 
             # Compute the 10-year rolling average
+            rolling_window = 10
             sliding_averages = (
                 df_model[indicator]
-                .rolling(window=10, min_periods=1)
+                .rolling(window=rolling_window, min_periods=rolling_window)
                 .mean()
                 .astype(float)
                 .tolist()
             )
             model_label = f"Model : {df['model'].unique()[0]}"
 
+            # Only add rolling average if we have enough data points
+            if len([x for x in sliding_averages if pd.notna(x)]) > 0:
+                # Sliding average dashed line
+                fig.add_scatter(
+                    x=years,
+                    y=sliding_averages,
+                    mode="lines",
+                    name="10 years rolling average",
+                    line=dict(dash="dash"),
+                    marker=dict(color="#d62728"),
+                    hovertemplate=f"10-year average: %{{y:.2f}} {unit}<br>Year: %{{x}}<extra></extra>"
+                )
 
         # Indicator per year plot
         fig.add_scatter(
@@ -117,17 +144,6 @@ def plot_indicator_evolution_at_location(params: dict) -> Callable[..., Figure]:
             marker=dict(color="#1f77b4"),
             hovertemplate=f"{indicator_label}: %{{y:.2f}} {unit}<br>Year: %{{x}}<extra></extra>"
         )
-
-        # Sliding average dashed line
-        fig.add_scatter(
-            x=years,
-            y=sliding_averages,
-            mode="lines",
-            name="10 years rolling average",
-            line=dict(dash="dash"),
-            marker=dict(color="#d62728"),
-            hovertemplate=f"10-year average: %{{y:.2f}} {unit}<br>Year: %{{x}}<extra></extra>"
-        )
         fig.update_layout(
             title=f"Plot of {indicator_label} in {location} ({model_label})",
             xaxis_title="Year",